from PIL import Image
import pytesseract
import argparse
import cv2
import os
 
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
	help="path to input image to be OCR'd")
ap.add_argument("-p", "--preprocess", type=str, default="thresh",
	help="type of preprocessing to be done")
args = vars(ap.parse_args())
# load the example image and convert it to grayscale
image = cv2.imread(args["image"])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
 
# check to see if we should apply thresholding to preprocess the
# image
if args["preprocess"] == "thresh":
	gray = cv2.threshold(gray, 0, 255,
		cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
 
# make a check to see if median blurring should be done to remove
# noise
elif args["preprocess"] == "blur":
	gray = cv2.medianBlur(gray, 3)
 
# write the grayscale image to disk as a temporary file so we can
# apply OCR to it
filename = "{}.png".format(os.getpid())
cv2.imwrite(filename, gray)
print(cv2);
text = pytesseract.image_to_string(Image.open(filename))
os.remove(filename)
print(text)
 
# show the output images
#cv2.imshow("Image", image)
#cv2.imshow("Output", gray)
cv2.waitKey(0)

def tess(img,process,type):

    # load the example image and convert it to grayscale
    image = cv2.imread(img)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     
    # check to see if we should apply thresholding to preprocess the
    # image
    if process == "thresh":
        gray = cv2.threshold(gray, 0, 255,
            cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
     
    # make a check to see if median blurring should be done to remove
    # noise
    elif process == "blur":
        gray = cv2.medianBlur(gray, 3)
     
    # write the grayscale image to disk as a temporary file so we can
    # apply OCR to it
    filename = "{}.png".format(os.getpid())
    cv2.imwrite(filename, gray)
    text = pytesseract.image_to_string(Image.open(filename),lang=type)
    os.remove(filename)
    return text
     
    # show the output images
    #cv2.imshow("Image", image)
    #cv2.imshow("Output", gray)
    #cv2.waitKey(0)

